9/18/2019 COPE WEBINAR SERIES FOR HEALTH PROFESSIONALS September - - PDF document

9/18/2019 1

COPE WEBINAR SERIES FOR HEALTH PROFESSIONALS

September 25, 2019 The Role of Executive Functioning in Behavioral Weight Loss Outcomes

Moderator: Lisa Diewald, MS, RD, LDN Program Manager MacDonald Center for Obesity Prevention and Education

• M. Louise Fitzpatrick College of Nursing

Nursing Education Continuing Education Programming Research

FINDING SLIDES FOR TODAY’S WEBINAR www.villanova.edu/COPE Click on Meghan Butryn Ph.D. webinar description page

Nursing Education Continuing Education Programming Research

DID YOU USE YOUR PHONE TO ACCESS THE WEBINAR?

If you are calling in today rather than using your computer to log on, and need CE credit, please email cope@villanova.edu and provide your name so we can send your certificate.

Nursing Education Continuing Education Programming Research

1 2 3

9/18/2019 2

OBJECTIVES

• 1. Describe the relationship between executive

function and lifestyle modification

• 2. Review the methods and results from a

recent study describing how executive functioning may predict weight loss and physical activity outcomes

• 3. Discuss clinical and practical implications

and future research directions

Nursing Education Continuing Education Programming Research

CE DETAILS

Villanova University College of Nursing is accredited as a provider of continuing nursing education by the American Nurses Credentialing Center Commission on Accreditation Villanova University College of Nursing Continuing Education/COPE is a Continuing Professional Education (CPE) Accredited Provider with the Commission on Dietetic Registration

Nursing Education Continuing Education Programming Research

CE CREDITS

• This webinar awards 1 contact hour for nurses and 1 CPEU for

dietitians

• Suggested CDR Learning Need Codes: 5370, 6000, 6010, 9020
• Level 2
• CDR Performance Indicators: 6.25, 8.1.2, 8.3.6

Nursing Education Continuing Education Programming Research

4 5 6

9/18/2019 3

The Role of Executive Functioning in Behavioral Weight Loss Outcomes

Meghan L. Butryn, PhD. Director of Research Center for Weight, Eating, and Lifestyle Science Drexel University

DISCLOSURE

Neither the planners or presenter have any conflicts of interest to disclose. Accredited status does not imply endorsement by Villanova University, COPE or the American Nurses Credentialing Center of any commercial products or medical/nutrition advice displayed in conjunction with an activity.

The role of executive functioning in behavioral weight loss

• utcomes

Meghan L. Butryn, PhD.

7 8 9

9/18/2019 4

Lifestyle Modification

• Recommended as a first line

treatment for individuals with obesity

• However, changing diet and exercise

behaviors is often challenging

• More research is needed to identify

individual‐level factors that facilitate

• r hinder weight‐related behavior

change.

Obesity and Executive Function

A growing body of literature suggests that a subset of top‐down cognitive processes, known as executive functions (EF), likely play a key role in the onset, development, and maintenance of obesity.

Executive Function

• Executive functions are

higher‐level cognitive processes that are critical for self‐regulation and goal‐

• riented behavior.

Organization Set Shifting Working Memory

10 11 12

9/18/2019 5

EF and Obesity

• Compared to normal weight controls, individuals with obesity

demonstrate poorer performance on a range of EF tasks (Dassen,

Houben, Allom, & Jansen, 2018; Fitzpatrick et al., 2013; Lavagnino et al., 2016; Martin & Davidson, 2014; Yang et al., 2018).

• There is a possible bidirectional relationship between EF and obesity,

with poor EF as both a risk factor and a consequence of obesity (Smith,

Hay, Campbell, & Trollor, 2011).

• Longitudinal studies also indicate improvements in EF following WL,

(Veronese et al., 2017) suggesting potential cognitive benefits to WL.

Weight Control and EF

• In our modern environment

highly palatable foods are

• mnipresent and sedentary

lifestyles are common.

• As such, weight regulation may

be particularly challenging for individuals with weaknesses in executive functioning.

Examples of Role of EF in Weight Control

Weight Control Goal Challenge EF

Limit Calorie Intake Good‐tasting foods that are readily available Enact inhibitory control by refraining from eating palatable food Achieve adequate energy expenditure Sedentary workplace and long commute leaves limited time for activity Use planning skills to create

• pportunities for physical

activity Make eating and exercise goals a priority Competing demands (e.g., related to family, career) may seem more pressing in the moment Attention and working memory are likely required to keep one’s long‐term goals in mind

13 14 15

9/18/2019 6

Your examples:

Organization Planning Problem solving Set shifting (switch from

• ne task to

another) Working memory (use relevant info in middle of activity) Inhibition

Eating behavior Physical Activity Other aspects

• f weight

control (e.g., attending treatment session, logging food)

EF and Weight Loss Outcomes

• Majority of evidence comes from child and adolescent samples

(Augustijn et al., 2018; Naar‐King et al., 2016; Nederkoorn, Jansen, Mulkens, & Jansen, 2007; Xu et al., 2017).

• In research with adult samples, two studies used a food‐specific

inhibitory control (IC) measure of EF to prospectively predict WL

• utcomes:
• Brockmeyer et al., 2016: food‐specific IC interacted with hedonic liking of food

to predict WL, such that low IC and high hedonic liking was associated with worse WL outcomes.

• Manasse et al., 2017: better performance on a food‐specific IC task at baseline

predicted greater percent weight loss at 12 months.

EF and Weight Loss Outcomes

• More research is needed to understand the multifaceted nature of EF

as it relates to WL outcomes. Only two prior studies measured multiple facets of EF in adults:

• Galioto et al., 2016: poorer set‐shifting and IC predicted worse 8‐week

percent weight loss outcomes in a medically‐supervised program using meal replacements.

• Dassen et al., 2018: better behavioral WM and self‐reported IC was

associated with greater 6m WL outcomes. Behavioral tasks measuring general and food‐specific inhibition and set‐shifting were not significantly associated with WL outcomes.

16 17 18

9/18/2019 7

EF and Physical Activity

• Engaging in PA leads to improved EF

(Guiney & Machado, 2013; Hugenschmidt et al., 2019; Moreau & Chou, 2019; Northey et al., 2018).

• However, it is unclear to what extent

baseline EF facilitates the adoption of PA.

• Prior research was conducted primarily

with older adults (Aartolahti, et al., 2015; Daly,

McMinn, & Allan, 2014; Gothe et al., 2014; McAuley et al., 2011) who may differ in

meaningful ways from the general population of WL‐seeking adults.

Summary

• Conceptual models of LM highlight the important role of EF in

inhibiting and initiating key weight‐related behaviors (Buckley et al.,

2014; Gettens & Gorin, 2017; Sutin et al., 2018).

• Prospective research is needed to examine how EF might predict

treatment outcomes in adults with obesity.

• Identifying pre‐treatment predictors of WL and PA may inform the

development of tailored interventions for individuals who are at risk for suboptimal outcomes.

Current Study

This study aimed to test the hypothesis that in a sample of OW/OB adults entering a lifestyle modification program, better EF at baseline would predict greater WL and PA after 6 months of treatment. Aimed to address gaps in the literature by:

a) Using a baseline measure of EF that was standardized, objective, and multi‐faceted. b) Objectively measuring changes in weight and physical activity.

19 20 21

9/18/2019 8

Participants

• Participants were recruited from the community for a clinical trial

(NCT02363010) of weight loss treatment

• BMI 27‐45 kg/m2
• 18‐70 years old
• No medical contraindications to participating and were physically able to begin

exercising

• Exclusion criteria:
• Hx of bariatric surgery, the use of weight‐affecting medication, >5% weight loss in the

past 6 months, or a diagnosis of major medical or psychiatric condition that would interfere with participation

• Women who were currently nursing, pregnant, or planning to become pregnant over

the course of the study

Intervention

• Group‐based lifestyle modification, 16 sessions over 6 months
• Treatment protocol adapted from Look AHEAD and Diabetes Prevention Program.
• Emphasized self‐monitoring of calorie intake as a core skill.
• Participants also learned stimulus control, problem solving, goal setting, and social

support skills.

• Weight loss goal = 10%
• PA goal = gradually increase to 250 minutes of MVPA per week

Measures

• Participant characteristics
• Reported age, gender, race, and ethnicity at baseline
• Weight
• Measured in clinic at baseline and 6 months using a Tanita model WB‐3000

digital scale

• Moderate‐to‐vigorous physical activity (MVPA)
• ActiGraph GT3X tri‐axial, solid state accelerometers
• Accelerometers were distributed to participants at baseline and 6 months,

with the instruction to wear them for the following seven consecutive days for all waking hours

• Bouted MVPA calculated (10 min or more per episode)

22 23 24

9/18/2019 9

Executive Functioning

• The tower test from the Delis‐Kaplan Executive Function System

(D‐KEFS) (Delis, Kaplan, & Kramer, 2001) was administered at baseline.

• Ppts were instructed to build towers using disks of various sizes in

as few moves as possible across 3 pegs.

• Rules: 1) May only move one disk at a time, 2) May never place a

larger disk over a smaller disk

• Total achievement score: number of moves to complete each
• tower. Represents “global” measure of EF.

Data Analysis Plan

• Multiple linear regression was used to predict weight loss at 6 months
• Due to the zero‐inflated distribution of MVPA, compound Poisson

linear model was chosen to predict MVPA at 6 months

• Post‐hoc exploratory mediation analysis was used to examine

whether MVPA at 6 months mediated the effect of baseline D‐KEFS scores on weight loss after 6 months of treatment.

• Effect sizes were reported as Cohen’s f2 in regression analysis and

Cohen’s d in t‐tests.

Data Analysis Plan

• 90% retention at 6‐month assessment
• Intent‐to‐treat approach
• Multiple imputation using MCMC algorithms known as chained

equations imputation (Yuan, 2005)

• Analysis results from multiply imputed data were combined using

Rubin’s rules (Rubin, 1987; Rubin, 1996)

25 26 27

9/18/2019 10

Baseline Characteristics

Mean (SD) or frequency Female 78% White 70% Black 25% Age 52.6 years (10.74) BMI 35.1 kg/m2 (4.63) MVPA 62.2 min/week (89.83)

D‐KEFS Baseline Associations D‐KEFS as a Predictor of Weight Loss

• Covariates: baseline BMI, baseline MVPA, 6‐month MVPA, and age
• Significant predictors of WL at 6 months:
• Total achievement score (f2 = 0.02, p = 0.04)
• Rule violations (f2 = 0.03, p = .002)
• Total completion time (f2 = 0.03, p = .005)
• Non‐significant:
• Mean first move time (p = 0.72)
• Time per move (p = 0.39)
• Move accuracy ratio (p = 0.16)

28 29 30

9/18/2019 11

Rule Violations Predicts Weight Loss

• t(313) = ‐3.78, p < .001, d =0.43
• No rule violations (n = 162) weight

loss = 11.0%

• Any rule violations (n = 158) weight

loss = 8.7%

Completion Time Predicts Weight Loss

• t(153) = ‐2.32, p = 0.022, d =0.37
• Lowest quartile of total completion

time (n = 80) weight loss = 11.0%

• Highest quartile of total completion

time (n = 80) weight loss = 9.0%

D‐KEFS as a Predictor of 6‐Month MVPA

• Covariates: baseline BMI, baseline MVPA, 6‐month WL, and age
• Significant predictors of MVPA at 6 months:
• Rule violations (f2 = 0.002, p = .036)
• Non‐significant:
• Total achievement score (p = 0.25)
• Mean first move time (p = 0.82)
• Time per move (p = 0.48)
• Move accuracy ratio (p = 0.37)
• Total completion time (p = 0.05) (trend)

31 32 33

9/18/2019 12

Rule Violations Predicts MVPA

• t(313) = 2.15, p = 0.032, d =0.33
• No rule violations (n = 162) 6‐month

MVPA = 169.8 min/week

• Any rule violations (n = 158) 6‐month

MVPA = 127.2 min/week

Exploratory Aim Results

• MVPA at 6 months significantly mediated the effect of rule violations
• n 6‐month WL
• Effect size = .11, bootstrap confidence intervals [0.04, 0.25]
• Participants with fewer rule violations on average had more

min/week of MVPA at 6 months, which in turn had a positive effect

• n 6‐month WL.

Discussion

• Pre‐treatment performance on several aspects of an EF task

significantly predicted weight and PA outcomes at 6 months of WL treatment.

• Certain facets of EF may influence the relative ease or difficulty

with which an individual changes their eating and physical activity behaviors.

• Contribution to the Literature
• First study to detect a predictive relationship between EF and
• bjectively measured PA in a WL‐seeking sample of adults
• One of the first to predict WL in adults using a behavioral

measure of EF that was broader than inhibitory control.

34 35 36

9/18/2019 13

EF predicts Weight Loss

• Weight loss was predicted by two of the four process measures:

rule violations and total completion time.

• Builds on prior research that has shown aspects of EF predicts WL in adults

(Dassen et al., 2018; Galioto et al., 2016; Manasse et al., 2017).

• Supports theory that limiting calorie intake in modern food environment

requires planning and inhibitory control skills (Applehans et al., 2016; Jansen et

al., 2015).

• Clinically notable effect: individuals with better EF performance

achieved >10% WL on average.

Rule Violations

• Rule violations at baseline predicted less WL at 6 months.
• Individuals with deficits in inhibitory control may be more prone

to dietary lapses (Manasse et al., 2014), particularly when faced with certain internal experiences such as tiredness or deprivation

(Crochiere et al., 2019).

• Because EF is necessary for initiating behaviors, these individuals

may also have lower utilization of skills designed to facilitate dietary restraint (e.g., self‐monitoring calorie intake, reducing tempting food cues, and ensuring that healthy foods are readily available).

Total Completion Time

• Longer completion time predicted less WL at 6 months.
• Prior research indicated that patients with PFC lesions have

slower completion times on the tower task compared to healthy controls (Yochim et al., 2009).

• Possible that slow performance is indicative of global executive

functioning weaknesses.

37 38 39

9/18/2019 14

EF predicts Physical Activity

• Clinically notable effect: difference of 40 min/week in 6‐month

MVPA for those with higher vs. lower EF at baseline.

• Builds on prior research that has shown that individuals with

poorer EF are less likely to adhere to PA intentions or prescriptions (Hall, Elias, et al., 2008; Hall, Fong, et al., 2008; McAuley,

Mullen, & Szabo, 2011).

• Weaknesses in EF may be an underappreciated barrier to the

adoption and maintenance of MVPA among adults with

• verweight or obese BMIs.

Rule Violations and MVPA

• MVPA at 6 months was predicted by baseline rule violations

aspect of EF, which is thought to reflect poorer inhibitory control and planning (Carey et al., 2008; Yochim et al., 2009).

• Given that many individuals with obesity report low enjoyment of

exercise (Ball, Crawford, & Owen, 2000), inhibitory control may be necessary to

• vercome temptations to engage in other behaviors rather than

exercising.

• In the modern environment where sedentary behavior is the default,

engaging in adequate levels of physical activity requires planning and problem‐solving (Hall and Fong, 2007).

Clinical Implications ‐ Assessment

• Pre‐treatment evaluation of EF may be useful for

identifying individuals at risk for suboptimal weight and MVPA outcomes, and allow for the development of targeted interventions

• Although further replication of results is necessary, the

findings from this study suggest that EF batteries should include measures of the inhibitory control and planning facets

• f EF.

40 41 42

9/18/2019 15

Clinical Implications ‐ Treatment

Interventions designed to compensate for or accommodate weaknesses in EF

• Habit learning strategies (i.e., to make

eating and exercise behaviors more automatic), thus requiring fewer executive resources (Berkman, 2018)

Interventions designed to improve EF

• Computerized cognitive training (Jones et

al., 2018) and gamified EF trainings (Verbeken et al., 2013; Dassen, Houben, Van Breukelen, & Jansen, 2018)

• Cognitive remediation therapy for obesity

(Raman et al., 2018)

• Research has begun to explore methods for tailoring lifestyle modification

for EF. While some findings are promising, further experimental research is needed.

Possibly most important implication?

• Empathy, compassion, humility
• Points to the complexity of lifestyle modification
• Constructs such as “motivation” or “willpower” are too basic in

understanding why some individuals engage in weight‐related self‐ regulation with ease and others struggle with behavior change

Strengths and Limitations

• Strengths
• Objective measurement of weight, MVPA, and EF
• Multidimensional measure of EF as opposed to only inhibitory

control

• Limitations
• Predominantly female sample
• Some domains of EF may not have been adequately captured
• Some possible confounds weren’t measured, e.g., general

cognitive ability

43 44 45

9/18/2019 16

Future Directions

• Utilize multiple measures of EF
• Identify weight loss strategies/behaviors that are most

impacted by inhibitory control and planning ability

• Develop effective strategies to address EF weaknesses and

improve treatment outcomes

• Does EF training that attempts to improve inhibition and planning

ability enhance outcomes in BWL?

• Other intervention components that set oneself up for success

(e.g., home environment change)

Thank you! mlb34@drexel.edu

• Look for an email containing a link to an evaluation. The email

will be sent to the email address that you used to register for the webinar.

• Complete the evaluation soon after receiving it. It will expire

after 3 weeks.

• You will be emailed a certificate within 2-3 business days.
• Remember: If you used your phone to call in, and want CE

credit for attending, please send an email with your name to cope@villanova.edu so you receive your certificate.

TO RECEIVE YOUR CE CERTIFICATE

46 47 48

9/18/2019 17

Villanova.edu/cope Upcoming FREE Continuing Education Webinar

A Proposed Standard of Care for Adult Obesity Treatment for All Providers

William Dietz, MD, Ph.D. Christine Gallagher, MPAff Wednesday, October 6, 2019 12:00PM - 1:00PM EST :

QUESTIONS & ANSWERS

Moderator: Lisa K. Diewald MS, RD, LDN Email: cope@villanova.edu Website: www.willanova.edu/COPE

49 50